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Magn Reson Med ; 81(3): 1849-1862, 2019 03.
Article in English | MEDLINE | ID: mdl-30499221

ABSTRACT

PURPOSE: This study explores the possibility of using a gradient moment balanced sequence with a quadratically varied RF excitation phase in the magnetic resonance fingerprinting (MRF) framework to quantify T2* in addition to δf , T1 , and T2 tissue properties. METHODS: The proposed quadratic RF phase-based MRF method (qRF-MRF) combined a varied RF excitation phase with the existing balanced SSFP (bSSFP)-based MRF method to generate signals that were uniquely sensitive to δf , T1 , T2 , as well as the distribution width of intravoxel frequency dispersion, Γ . A dictionary, generated through Bloch simulation, containing possible signal evolutions within the physiological range of δf , T1 , T2 , and Γ , was used to perform parameter estimation. The estimated T2 and Γ were subsequently used to estimate T2* . The proposed method was evaluated in phantom experiments and healthy volunteers (N = 5). RESULTS: The T1 and T2 values from the phantom by qRF-MRF demonstrated good agreement with values obtained by traditional gold standard methods (r2 = 0.995 and 0.997, respectively; concordance correlation coefficient = 0.978 and 0.995, respectively). The T2* values from the phantom demonstrated good agreement with values obtained through the multi-echo gradient-echo method (r2 = 0.972, concordance correlation coefficient = 0.983). In vivo qRF-MRF-measured T1 , T2 , and T2* values were compared with measurements by existing methods and literature values. CONCLUSION: The proposed qRF-MRF method demonstrated the potential for simultaneous quantification of δf , T1 , T2 , and T2* tissue properties.


Subject(s)
Brain/diagnostic imaging , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Radio Waves , Algorithms , Artifacts , Healthy Volunteers , Humans , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Pattern Recognition, Automated , Phantoms, Imaging , Reproducibility of Results , Signal-To-Noise Ratio
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